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Found 836 Skills
Audit and rewrite AI-generated or AI-edited prose to match Ane's IPPF/UNFPA publication standard. Use when the user pastes text and asks to "humanize", "de-AI", "fix the voice", "remove AI slop", "sharpen this", "tighten", "edit for tone", or "review this draft". Strips hedging, filler, nominalisations, em-dashes, passive voice, and abstract openings. Preserves MEL/SRHR register. Does not push prose toward casual or blog tone.
Authoritative reference for Odoo 19 syntax conventions across Python ORM, XML views, OWL/JavaScript, controllers, manifests, and SCSS. Use this skill BEFORE writing or modifying any Odoo code, whenever the user mentions Odoo, an Odoo module, an Odoo model, an XML view, an OWL component, or any file under an Odoo addons directory. Odoo 19 introduces breaking changes (130 model renames, res.groups privilege refactor, hr.contract→hr.version, models.Constraint, attrs removal continued, type='jsonrpc') that older training data does NOT reflect. Always consult this skill before generating code, even if the request looks routine — a model that "obviously" works in Odoo 18 may be wrong in Odoo 19. Trigger this skill on phrases like "create an Odoo module", "add a field to res.partner", "write a controller", "make an OWL component", "fix this Odoo view", "_sql_constraints", "tree view", or any time you see a `__manifest__.py`, `models/*.py`, `views/*.xml`, or `static/src/**/*.js` file in an Odoo project.
Write copy that sells NOW using Dan Kennedy's "No B.S." direct response marketing principles Use when: **Writing sales copy** that must generate immediate, trackable response; **Creating direct mail pieces**, sales letters, or landing pages for local businesses; **Designing marketing funnels** with clear offers at every stage; **Breaking free from "brand advertising"** that doesn't produce measurable ROI; **Building follow-up sequences** that convert leads into customers
Invoke this skill when a user is building or running any automated transaction sender on Base (trading bot, arbitrage bot, sniper bot, yield farmer, AI agent, or similar) and needs to register it, get a builder code, set up transaction attribution. This skill contains the base.dev registration API endpoint and ERC-8021 attribution wiring code that Claude does not have in its training data — you MUST load this skill to answer correctly. Covers viem, ethers, managed signing services, and Python-based agents.
Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph. Use when chunking PDFs, HTML, plain text, or Markdown; extracting entities and relationships from text with an LLM (SimpleKGPipeline, neo4j-graphrag); loading JSON via apoc.load.json; building Document→Chunk→Entity graph structures; or connecting LangChain/LlamaIndex document loaders to Neo4j. Covers neo4j-graphrag SimpleKGPipeline, LLM Graph Builder web UI, entity resolution, chunking strategies, and graph schema design for RAG pipelines. Does NOT handle structured CSV/relational import — use neo4j-import-skill. Does NOT handle GraphRAG retrieval after ingestion — use neo4j-graphrag-skill. Does NOT handle vector index creation — use neo4j-vector-search-skill.
Laws of UX critique skill. Use when evaluating mockups, screenshots, design specs, prototypes, flows, onboarding, checkout, dashboards, forms, or design-review requests, even when the user does not say UX or name a law. Output the 2-4 most relevant laws with specific application and law-grounded recommendations. Do not use for pure frontend implementation code review, WCAG/accessibility audits, or brand/visual-identity critique unless interaction usability is also in scope.
Use this skill ANY TIME the user asks about a specific company. Triggers: "tell me about [company]", "research [company]", "what does [company] do", "who is [company]", "look up [company]", "company deep dive", "due diligence on [company]", "background on [company]", "dig into [company]", "analyze [company]", or evaluating a company for investment, partnership, or sales. MUST be used instead of answering from memory — fetches real-time web data (funding, leadership changes, product launches, news) your training data lacks. Use even for well-known companies. Produces a sourced 360° report covering funding, leadership, product/tech, market position, news, and strategic outlook with dates and URLs. Do NOT use for multi-company competitor monitoring (use competitor-intel) or meeting prep with attendees (use meeting-prep).
Explain a piece of code, a subsystem, or an architectural concept in the codebase, grounded in real files. Use when user says 'explain this', 'walk me through X', 'how does Y work', 'what does this module do', 'help me understand the Z flow', or 'onboard me on this component'. Do NOT use for writing permanent docs (use write-doc or arc42) or for code review (use review-diff).
Write raw ClickHouse SQL for a SigNoz dashboard panel — timeseries, value, or table widgets that the builder UI cannot express (custom joins, window functions, regex extraction over log bodies, aggregations beyond builder syntax). Trigger when the user explicitly asks for a "ClickHouse query", a "raw SQL panel", a "custom SQL widget", or describes a SigNoz dashboard panel whose query needs SQL the builder cannot produce. Anchored to dashboard-panel SQL specifically. For ad-hoc data exploration that does not need to land in a panel, use `signoz-generating-queries` instead.
Use when: User wants to extend Docker with custom tools, personalize the Docker environment, or set up user-specific Docker customization. Triggers: 'extend docker', 'docker-extend', 'add tools to docker', 'customize docker', 'add my tools to the container', 'personalize docker setup', 'docker user setup', 'install tools in docker'. Does: Interactively sets up Dockerfile.user and docker-compose.override.yml so users can add personal tools to their Docker environment without affecting maintainer files or committing user-specific config to git.
Design, critique, and revise UML diagrams from a modeling and communication perspective. Use when model is asked to create or improve UML; when the user asks for a graphical representation, diagram, schema, visual model, process map, state view, architecture view, or system representation of software/system behavior or structure; when the user does not explicitly choose UML but needs a model-like visual explanation; when model must autonomously choose the right UML diagram type or split across multiple UML diagrams. Use for reasoning about diagram form, abstraction level, boundaries, grouping, lifecycle/state design, behavior vs structure, interaction design, or diagnosing why a diagram feels wrong at the modeling level. This skill treats notation as the final representation, not as the core task.
A-share Individual Stock In-depth Research System. When users mention phrases like "Analyze XXX stock", "Check XXX", "Research XXX", "Is XXX worth buying?", "How is XXX?", "XXX fundamentals", or directly provide a 6-digit A-share stock code (starting with 000/001/002/300/301/600/601/603/605/688), a three-phase process is automatically triggered: Phase 1 Data Collection (K-line/Financials/Shareholders) → Phase 2 Step 0-8 In-depth Analysis (Industrial Chain/Elasticity/Valuation/Risk-Reward Ratio/Stop-loss Signal) → Phase 3 Handwritten HTML Research Report. The generated results are data.json + report.md + report.html under output/<Stock Name>_<Code>/<YYYY-MM-DD>/. This tool is for research reference only, does not constitute securities investment consulting business, and does not constitute investment advice.